Restricting hierarchical posts with social network metrics methods and apparatus

ABSTRACT

A method for a computer system includes receiving a listing from a first user, determining a first plurality of social network relationship factors for the first user with respect to a first plurality of users, determining a second plurality of users from the first plurality of users who fulfill a filtering criteria, wherein a third plurality of users from the first plurality of users do not fulfill the filtering criteria, and making the listing available to users from the second plurality of users but not the third plurality of users, and providing the listing to a second user from the second plurality of users.

CROSS REFERENCE TO RELATED APPLICATIONS

The present invention claims priority to Provisional Application No.60/560,414 filed Apr. 7, 2004 and incorporates it by reference for allpurposes. The present invention also incorporates by reference, for allpurposes Provisional Application No. 60/560,468 filed Apr. 7, 2004 andProvisional Application No. 60/570,911 filed May 12, 2004.

BACKGROUND OF THE INVENTION

The present invention relates to trust-metric networks. Morespecifically, the present invention relates to methods and apparatus forusing trust relationships within social networks to organizehierarchical posts such as classified listings.

The term “classified listings” has typically been associated with pagesand pages of tiny print in newspapers. These listings include helpwanted listings, items for sale, wanted items, houses and apartments forrent, services offered, and the like. Many such listings are posted byindividuals, companies, groups, etc.

Typical problems with the traditional classified listings includes thatif a buyer is looking for something in particular, the buyer mustconstantly devote time pouring over pages and pages of classifiedlistings. Another problem is that if a listing is misclassified, buyersmay not see them. Yet another problem is that classified listings oftencontinue to run, even after the item is sold, for example. Additionalproblems will be discussed below.

With the advent of wide area computer networks, such as the Internet,attempts have been made to bring classified listings on-line. Oneadvantage to on-line classified listings over paper-based listings isthat buyers are often provided with key-word searching capability tolocate potentially relevant classified listings. Another advantage isthat when an item is sold, for example, the advertisement can bepromptly removed from the classified listings.

Drawbacks to on-line classified listings include that buyers or sellersare often wary of each other. Except for an e-mail address, it is oftendifficult for buyers or sellers to judge whether the other party is“legitimate.” For example, when buying an expensive item such as a RolexDaytona watch via a classified listing, buyers are concerned whether thewatch is genuine, whether the watch works, whether they will actuallyget the watch if they send a payment, or the like. This is especiallyrelevant when the seller is an individual. When the seller is abusiness, for example, buyers may have a little more sense ofconfidence. These drawbacks also apply to traditional classifiedlistings.

Examples of on-line classified listings services includes e-commercebased web sites, such as shopping.yahoo.com, froogle.com, amazon.com,ebay.com, overstock.com, epinions.com and the like. In such services, arating system is typically provided for both the seller and the buyer torate each other. The rating system thus provides subsequent buyers andsellers some indication of the reputation of the respective sellers orbuyers, or how happy they were with the transaction.

Problems with the rating systems include the use of “shill” buyers orsellers, who rate transactions highly, although no actual transactiontook place. Such shills are typically related to or work for the ratedparty. Because of such shills, the ratings of buyers or sellers reportedon various web sites may not be reliable.

Another problem with the rating system is that it inherently favorsvolume buyers or sellers (e.g. businesses) over individuals. Forexample, all things being equal, a buyer would probably buy from abusiness seller with 500 ratings that are good rather than an individualseller with only one rating, an excellent rating.

Very similar issues also apply to users who post classified listings.For example, is the buyer trustworthy, will the buyer pay, is thebuyer's rating accurate, and the like.

Accordingly, in light of the above, what is desired are methods andapparatus that provide classified listings without the drawbacks toindividuals, as discussed above.

BRIEF SUMMARY OF THE INVENTION

The present invention relates to methods and apparatus for usingtrust-metrics in a trust-metric network to organize classified listings.With embodiments of the present invention, trust relationships betweenusers in trust-metric networks, such as social networks, are used tohelp specify the reach of classified listings in the network as well asto help users manage or prioritize which the classified listings areviewed.

According to one aspect of the invention, a hierarchal posting method isdisclosed. On technique includes determining a plurality of socialnetwork relationships for a first user within a social network, andreceiving a hierarchal listing from the first user. The process may alsoinclude determining which users in the social network can view thehierarchal listing in response to the plurality of social networkrelationships for the first user.

According to another aspect of the invention, a computer system isdisclosed. One apparatus includes a plurality of social networkrelationships for a first user. The system may also include a processorconfigured to receive a hierarchal listing from the first user, andconfigured to determine which users in the social network can view thehierarchal listing in response to the plurality of social networkrelationships for the first user.

According to yet another aspect of the invention, a computer programproduct is disclosed. One computer program product may include code thatdirects the processor to receive a plurality of social networkrelationships for a first user, and code that directs the processor toreceive a hierarchal listing from the first user. Additionally, acomputer program product may include code that directs the processor todetermine a subset of users in the social network can view thehierarchal listing in response to the plurality of social networkrelationships for the first user, and code that directs the processor toprovide the hierarchal listing to the subset of users. The codes may bemachine readable or human readable. The codes may reside on a tangiblemedia such as a optical media (e.g. CD, DVD), magnetic media (e.g. harddisk), semiconductor media (e.g. RAM), or the like.

According to another aspect of the invention, a method for a computersystem is disclosed. One technique includes receiving a listing from afirst user, determining a first plurality of social network relationshipfactors for the first user with respect to a first plurality of users,and determining a second plurality of users from the first plurality ofusers who fulfill a filtering criteria, wherein a third plurality ofusers from the first plurality of users do not fulfill the filteringcriteria. Additional techniques include making the listing available tousers from the second plurality of users but not the third plurality ofusers, and providing the listing to a second user from the secondplurality of users.

According to another aspect of the invention, a computer system computersystem is disclosed. One apparatus includes memory configured to storerelationships between a first plurality of users. Another systemincludes a processor coupled to the memory wherein the processor isconfigured to receive a first classified advertisement listing from afirst user, wherein the processor is configured to determine a socialnetwork criteria, wherein the processor is configured to determine asecond plurality of users from the first plurality of users who fulfillthe social network criteria, wherein the processor is configured toprovide the first classified advertisement listing to users from thesecond plurality of users, wherein the processor is configured tosuppress the first classified advertisement listing from users from athird plurality of users from the first plurality of users who do notfulfill the social network criteria.

According to yet another aspect of the invention, a computer programproduct for a computer system including a processor is disclosed. Onecomputer program product includes code that directs the processor todetermine an advertisement listing from a first user, code that directsthe processor to determine a first plurality of social networkrelationship factors for the first user with respect to a firstplurality of users, and code that directs the processor to determine asecond plurality of users from the first plurality of users who fulfilla filtering criteria, wherein a third plurality of users from the firstplurality of users do not fulfill the filtering criteria. Other computerprogram product may include code that directs the processor to determinerequests for advertisement listings from users from the first pluralityof users, and code that directs the processor to provide theadvertisement listing to the users from the second plurality of users inresponse to the requests, but not to users from the third plurality ofusers in response to the requests. The codes may reside on a tangiblemedia such as a optical media (e.g. CD, DVD), magnetic media (e.g. harddisk), semiconductor media (e.g. RAM), or the like.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to more fully understand the present invention, reference ismade to the accompanying drawings. Understanding that these drawings arenot to be considered limitations in the scope of the invention, thepresently described embodiments and the presently understood best modeof the invention are described with additional detail through use of theaccompanying drawings in which:

FIG. 1 illustrates a block diagram according to an embodiment of thepresent invention;

FIG. 2 illustrates another block diagram according to an embodiment ofthe present invention;

FIGS. 3A-B illustrate a block diagram of an embodiment of the presentinvention; and

FIGS. 4A-B illustrate another block diagram of an embodiment of thepresent invention.

DETAILED DESCRIPTION OF THE INVENTION

The following definitions are used in the present application todescribe embodiments of trust-metric networks. That is, networks ofusers (e.g. persons, businesses) that have relationships between themthat specify or imply a measure of trust or bond between users. Thefollowing terms are particularly relevant for social networkembodiments.

Classified Listing—An offering for goods, services, job openings, openauctions, or the like typically originated by an individual user, anorganization, or the like. The offerings are typically classifiedaccording to a hierarchy.

Home page—Typically the first page presented to a user when the userlogs into the social network. Home pages may or may not be customizedfor each user.

People Card—A profile page associated with a user. A profile pagetypically includes a description of information provided by the user andretrievable by other users/viewers. This may include a name, contactinformation, a list of immediate friends, a list of interests, a list ofaffinity groups the user is a member of, job title, employer, and thelike. In embodiments of the present invention, the amount of informationdisplayed to a user/viewer may vary according to any number ofparameters. Users may, for example specify the amount of userinformation viewable to other users depending upon metrics between theuser and the other users. As examples, the user may provide a firste-mail address to users at a close social distance (defined below) (e.g.1), and a second e-mail address to users farther away; the user mayprovide their full name to users less than a social distance of 2.0, butonly their first name to other users; the user may allow users closerthan a social distance of 3.2, to view a photo album, but the photoalbum is hidden to distant users; and the like.

In the various embodiments, users may have full control of what type ofinformation they provide, according to their relationships in the socialnetwork. In some embodiments, there is a default relationship betweenthe type of information provided about a user with respect to theirrelationships (e.g. social distance). The default relationships may beoverridden by the user.

In various embodiments, users may have one or more profiles, forexample, a profile for an alumni affinity group, a profile for theirbusiness, a profile for close friends. In various embodiments, differentprofiles may include different types of information about the user.

Degrees of Social Separation—A value defined as immediate friends (oracquaintances) of a user being a first degree; friends of the user'simmediate friends being a second degree; etc. Degrees of SocialSeparation may also be computed relative to affinity groups, withmembers of the same affinity group being a first degree; members ofdirectly related affinity groups being a second degree; etc. Degrees ofsocial separation may also refer to a combination of relationships orties between friends and relationships or ties between members ofaffinity groups.

In various embodiments, the degree of social separation betweendifferent users may be different depending upon which metric forseparation distances are used, and depending upon the context in whichthe separation distance is to be used. Additionally, users may havedifferent social separations for different user profiles. For example,two users may have a large social separation when considering personalprofiles, but a small social separation when considering membershipprofiles in affinity groups. In some embodiments, the social distancemay be the shortest distance between a first user and a second user.

Social distance—A numeric value associated with the Degrees of SocialSeparation between a first user and a second user. In embodiments of thepresent invention, a smaller social distance between users represents ahigher “trust” level between the users. For example, in many cases, auser will trust her immediate friends (social distance=1); however, auser will trust a friend of her immediate friend (social distance=2) toa smaller degree; and a user will trust a friend of a friend of herimmediate friend (social distance=3) even less; and so on. In variousembodiments, social distance need not be an integral value and may be afloating point number, for example social distance=4.2, socialdistance=1.5, etc. In such embodiments, other weighting factors otherthan mere degree of social separation may be considered, such as“importance” of the relationships between the users, the frequency ofcommunications between the users, the quality of business relationshipbetween the users, and the like. Other types of “fuzzy” weightingfactors may include frequency of communication between users, commonposts to similar forums, and the like, as will be described below.

In embodiments of the present invention, social distance may besymmetric or asymmetric numbers. As an example of this, a socialdistance between user A and user B may be the same (e.g. 1.4), when bothuser A and user B value their relationship the same. However, if user Avalues the relationship more than user B, the social distance from userB to user A may be smaller (e.g. 1.3) than from user A to user B (e.g.1.8). Some of the factors described above may be used to determineweighting of the relationships, including user satisfaction of priorinteractions, responsiveness to correspondences or queries, performance,common interests, common posting forum, a “frequency” factor, and thelike.

In various embodiments, frequency factors may be based upon the number(or percentage) of contacts between two users. For example, the morefrequently the two users exchange messages, the more heavily weighted isthe frequency factor for the two users. These frequency factors mayresult in non-integer social distances. In various embodiments, anassumption is made that users who communicate frequently may be closerbetter friends. For example, user A has a social distance of 1.3 fromuser B, and user B frequently communicates with user C, but not user D.Accordingly, in one embodiment, the computed social distance betweenuser A and user C may be 1.9 which would be smaller than the socialdistance between user A and user D which may be 2.4.

As is described in the above-referenced provisional application, inembodiments of the present invention, the social map of a user may becomputed in real time or near real-time, when the user logs into thesocial network.

In various embodiments, relationship weighting factors may be manuallyentered by the user. For example, user A may rate a concludedtransaction between user A and user B; user B may rate the timeliness ofuser A payment speed; and the like. In alternative embodiments, therelationship weighting factors may automatically be determined. Forexample, the frequency of communications between users may indicate amore valued relationship between the users, accordingly, the socialdistance between users may be shortened. In other examples, the morefrequently two users post messages to an affinity group forum or postmessages on the same thread in the forum, the higher their weightingfactor relative to each other. In such embodiments automaticallyincreasing weighting factors between the users is useful because itinfers that users have shared interests. Other types of inferences basedon user behavior are contemplated in other embodiments.

In other embodiments, users can decrease their social distance to otherusers by their own actions. For example, by quickly responding to e-mailmessages, or other communications, responsiveness weighting factor of auser may be increased; as another example, frequency of checking e-mailmessages or logging into the social network, or the like may increase aresponsiveness factor. As an example, if a user runs a business usingthe social network, by increasing her quality of service, and clientsatisfaction, her reputation factor may increase. Accordingly, socialdistances of users relative to the business in the social network mayautomatically decrease, because of her increased reputation.

Tribe—An affinity group. One example is similar to a Usenet group,having a user moderator, user participants, discussion forums, etc;whereas in other examples, an affinity group need not have a moderator,leader, or the like. In embodiments of the present invention, two usersmay be connected in the social network by being members of the sameaffinity group, even though the two users may otherwise have a largesocial distance between them.

In various embodiments of the present invention, Tribe membership may beexplicitly defined or implicitly defined. Accordingly, Implied Tribesmay be determined. These tribes are groupings of users based on a commoninterest, common activity, or any other type of trait held by two ormore users, without an explicit definition. Examples of implied tribesmay include users who list a common interest, such as “skiing,” userswho view a particular classified listing, restaurant review, or thelike.

In some embodiments of the present invention, members of affinity groupsor groups of users are logically organized as one user (super node). Insuch embodiments, relationships of members are collapsed and imputed tothe affinity group. For example, a clique of three close friends may beconsidered a super node, for sake of simplicity when performingrelationship computations. The relationships of the super node mayinclude the relationships of its underlying users. For example, a skiUtah affinity group may have users A, B, and C, thus the ski Utahaffinity group super node will have the affinity relationships of itsusers A, B, and C. Accordingly, affinity groups can have socialdistances from other affinity groups. In another example, the ski Utahaffinity group will combine the personal relationships of its users A,B, and C. In various embodiments, for this example, the ski Utahaffinity group will list both the ski Utah affinity group relationshipsand the ski Utah affinity group personal relationships side-by-side.These relationships may be represented by a graph, or as desired. Inother embodiments, the relationships of the affinity group are expandedand imputed back to the members of the affinity group.

Tribe Mapping—A process of determining a bottom-up taxonomy for relatedtribes based on common user membership overlap. These maps may becomputed based upon explicit tribe membership data, or implicit tribemembership, as described above. For example, if 75% of the users in abird-watching tribe also view classified listings on spotting scopes, atribe mapping may closely associate the bird-watching tribe with animplied spotting-scope tribe. As another example, a “San Francisco WineDrinker” tribe will most likely have a significant overlap with a “SanFrancisco” tribe, and a “Wine Drinker” tribe. This mapping can beperformed automatically through algorithms that compute similarity, ormanually by moderators of the tribes, who explicitly state theirrelationship. Accordingly, overlap of affinity groups may be explicit orimplicit. The relationship between tribes can then be used as part of asocial network filter or affinity filter criteria, described furtherbelow.

User Network—A subset of all users on the social network. In embodimentsof the present invention, a User Network may be socially limited to aspecified social distance from the user and/or by affinity groups whichthe user is a member of. For example, a user network may include allusers within a social distance (or affinity distance) of 3.5.

In other embodiments, the user network may constrain the type ofinformation available to the user. As examples, users may be constrainedto searching for information (e.g. job posts) from users only withintheir user network; users may be limited to sending e-mails orinvitations, or chatting only with other users in their user network.Many other restrictions can be envisioned to be placed on users basedupon their relationships in the social network.

Social Map—A map of connections to other users on the system. The Socialmap typically includes a shortest path between two users, either viafriendship, affinity group, or the like. The social map is typicallysocially limited to a specified social distance from the user. Inembodiments of the present invention, the limited distance may bespecified by an administrator, the user, or the like.

Social Network—A network of relationships between users (via friendship,affinity, or the like).

People Web—A unified collection of social networks into a completesocial map. Unifying identities across social networks allows one totraverse the social map in a way similar to DNS for network traffic.

FIG. 1 is a block diagram of typical computer system 100 according to anembodiment of the present invention.

In the present embodiment, computer system 100 typically includes amonitor 110, computer 120, a keyboard 130, a user input device 140, anetwork interface 150, and the like.

In the present embodiment, user input device 140 is typically embodiedas a computer mouse, a trackball, a track pad, wireless remote, and thelike. User input device 140 typically allows a user to select objects,icons, text and the like that appear on the monitor 110.

Embodiments of network interface 150 typically include an Ethernet card,a modem (telephone, satellite, cable, ISDN), (asynchronous) digitalsubscriber line (DSL) unit, and the like. Network interface 150 aretypically coupled to a computer network as shown. In other embodiments,network interface 150 may be physically integrated on the motherboard ofcomputer 120, may be a software program, such as soft DSL, or the like.

Computer 120 typically includes familiar computer components such as aprocessor 160, and memory storage devices, such as a random accessmemory (RAM) 170, disk drives 180, and system bus 190 interconnectingthe above components.

In one embodiment, computer 120 is a PC compatible computer having oneor more microprocessors from Intel Corporation, or the like. Further, inthe present embodiment, computer 120 typically includes a UNIX-basedoperating system.

RAM 170 and disk drive 180 are examples of tangible media for storage ofdata, audio/video files, computer programs, user profile card data, usersocial network-related data, social distance computation programs,hierarchal posting data, social network filtering criteria, otherembodiments of the present invention and the like. Other types oftangible media include magnetic storage media such as floppy disks, harddisks, removable hard disks; optical storage media such as CD-ROMS,DVDs, bar codes, holographic; semiconductor memories such as flashmemories, read-only-memories (ROMS), volatile memories; networkedstorage devices; and the like.

In the present embodiment, computer system 100 may also include softwarethat enables communications over a network such as the HTTP, TCP/IP,RTP/RTSP protocols, and the like. In alternative embodiments of thepresent invention, other communications software and transfer protocolsmay also be used, for example IPX, UDP or the like.

FIG. 1 is representative of computer rendering systems capable ofembodying the present invention. It will be readily apparent to one ofordinary skill in the art that many other hardware and softwareconfigurations are suitable for use with the present invention. Forexample, the use of other micro processors are contemplated, such asPentiumIV™ or Itanium™ microprocessors; AthlonXP™ microprocessors fromAdvanced Micro Devices, Inc; PowerPC G4™, G5™ microprocessors fromMotorola, Inc.; and the like. Further, other types of operating systemsare contemplated, such as Windows® operating systems (e.g. WindowsXP®,WindowsNT®, or the like) from Microsoft Corporation, Solaris from SunMicrosystems, LINUX, UNIX, MAC OS from Apple Computer Corporation, andthe like.

FIG. 2 illustrates another block diagram according to an embodiment ofthe present invention. FIG. 2 includes a server 200 coupled to adatabase 210 and coupled to a graphing system 220. A plurality of users230 are coupled to server 200 via a network 240, such as the Internet.

In the present embodiments, users 230 may be any conventional accessdevice, such as a computer, a web-enabled telephone, a personal digitalassistant, or the like. In operation, users 230 log into server 200 andthen makes one or more requests for data. The data that is returned istypically displayed back to user.

In various embodiments, server 200 may be embodied, as described above,and include one or more servers (e.g. server cluster) that respond torequests from users 230. For example, multiple servers may be used inembodiments where server performance is important, e.g. East Coastserver for client requests from Boston, Midwest server for clientrequests from Chicago, and the like. Server 200 may be configured asillustrated in FIG. 1, above.

Database 210 may be any conventional database such as powered by MySQL,Oracle, Sybase, or the like. In other embodiments, database 210 may beany other data source such as an LDAP server, or the like. In thepresent embodiment, database 210 is configured to store and maintainuser data, to store and maintain relationship data between the users,and configured to make changes to relationship data between users, amongother functions. As illustrated, database 210 may be coupled to server200 and to graphing system 220 to send and receive respective data, aswill be described below.

In various embodiments, graphing system 220 is a stand-alone computersystem configured to receive data from server 200, and configured tostore and maintain relationship data between the users. Additionally, invarious embodiments, graphing system 220 is configured to determine andprovide requested relationship data to server 200. In variousembodiments, graphing system 220 may be integrated as a part of server200, or the like.

In various embodiments, graphing system 220 may be a conventionalcomputer system, as described above. In one embodiment, graphing system220 maintains in the relationship data of users (adjacency information)in RAM. In other embodiments of the present invention, graphing system220 may store a portion of the relationship data of users in RAM. Theother portions of the relationship data of users may be stored onmagnetic disk or other media, on database 210, or the like. In suchembodiments, elements of the relationship data of users can be loadedinto a most recently used (MRU) queue.

In the present embodiment, graphing system 220 computes socialrelationships in real time by minimizing lookup time of requiredinformation. For example, lookup operations such as: who are the directfriends of person A?, who are the members of tribe B?, etc, arepreformed in constant or near constant time. Additionally, graphingsystem 220 stores relationship data for users in RAM in a way thatallows explicit control over memory allocation. In some embodiments ofthe present invention, it is expected that graphing system 220 will beable to compute social distance computations on a social network of upto 20 million users, within 20 milliseconds or less.

In embodiments of the present invention, graphing system 220 may includea number (e.g. cluster) of individual systems. In various embodiments,the individual systems may store unique portions of the relationshipdata of users; the individual systems may store in parallel the sameportions (or the entire) relationship data of users; or the like. Anytraditional data clustering technique may be used to implement graphingsystem 220 in embodiments of the present invention.

Additionally, in embodiments, graphing system 220 determines thespecific relationships (e.g. social distance queries) primarily in RAM.With such a configuration, the performance of graphing system 220 hasproven superior than disk-based computation systems such as conventionaldatabases.

In various embodiments, graphing system 220 includes four softwarecomponents including two C++ components, and two Java components. Inother embodiments, other architectures are envisioned. The C++components includes a portion that solves social distance queries usingthe RAM, utilizing a memory efficient graph implementation, as will bediscussed below. Additionally, the C++ components includes a daemonprocess that reads commands and write results to a socket (or othertransport medium). By having graphing system 220 respond to relationshipqueries via a socket, different implementations of the server interface,may be easily used, without touching the C++ components.

In various embodiments, the server interface, i.e. java components,includes a java class that provides APIs to requesting servers, such asserver 200. The API's serve as the interface layer to the C++components. Additionally, the java components includes an interfacelayer that sends requests to the socket and waits for relationship dataon the socket.

In implementation, graphing system 220 may be multithreaded and thus cansupport simultaneous requests from server 200. Additionally, in caseswhere server 200 includes one or more servers for increasing scale,standard clustering techniques such as data replication can be used tosupport simultaneous requests from one or more servers.

In various embodiments, many different types of relationship data can bedetermined by database 210 and graphing system 220 including, a shortestpath between user A and user B (e.g. SOCIAL_DISTANCE (A,B)), typically afloating point value reflecting the distance from user A to B; shortestpaths between user A and user B, for example through user C and user D,or through user E and user F (returned as an array of paths); what usersare within or less than N degrees from user A (less than a N socialdistance); who is the most connected user in the social network, and thelike. Many other types of information are reportable within otherembodiments of the present invention. In embodiments of the presentinvention, database 210 and graphing system 220 may communicate witheach other via custom function calls from database 210.

The relationship determined may be filtered and sorted in any number ofconventional ways based upon various parameters. Additionally, database210 and graphing system 220 are enabled to received up-datedrelationship data, such as adding a new user/friendship relationship orremoving a friendship relationship, and to recompute the relationshipdata, and the like.

FIGS. 3A-B illustrate a flow chart according to an embodiment of thepresent invention. More specifically, FIGS. 3A-B illustrate a process ofrestricting display of postings by using trust-based metrics.

Initially, any number of users log into the social-network server 200,step 300. Such operations may be done with conventional username/password combination, or any other level of security. As an optionto the users, the users submit hierarchal posts, step 310. For example,in various embodiments, a first, a second, and a third user submitfirst, second, and third hierarchal posts to server 200, respectively.In various embodiments, a server, separate from server 200 may be usedto receive the hierarchal posts. In various embodiments, hierarchalposts are typically classified listings, as discussed above, offeringgoods or services, listing job openings, listing auction entries, andthe like. The posts are associated with the submitting users, andstored, step 320. In various embodiments, various memory pointers may beused to associate the poster with the post.

In various embodiments, the user must belong to the social network inorder to view classified listings. This is desirable in order to expandthe social network and to provide the values for the filtering criteriafor the classified listings (e.g. geographic location, socialdistances). Subsequently, a user (e.g. buyer or potential buyer) logsinto the social-network server 200, step 330. In response, in oneembodiment, server 200, database 210 and graphing system 220,dynamically performs a social network calculation, and determines asocial map for the buyer user, step 340. As discussed above, in variousembodiments, the social map may include a limited number of users,typically users who are within a pre-determined social distance from thebuyer. For example, the pre-determined social distance may be a number,such as 3.5, 2.0, or the like. In another embodiment, the social map mayinclude a fixed number of users, such as 50 of the closest (via socialdistance) users. In still other embodiments, combinations of the abovemay be used. For example, a displayed list may include users within asocial distance of 1.5 but limited to the first 20 or the closest 20. Asdiscussed in the referenced application above, this calculation can beperformed in real-time.

In the various embodiments, the potential buyer is automaticallypresented with their home page, step 350. The home page may include aset or sub-set of users (e.g. friends) in the social map, theon-line/off-line status of those friends, and the like. Otheroptions/features on their home page may include adding/deleting membersto a social network, adding/deleting affinity group memberships,changing the user's profile card, viewing recommendations,sending/receiving e-mail messages, and the like.

In various embodiments, the social map determined in step 340 mayinclude users at a greater social distance than is presented to the userin step 340. For example, the social map may be determined to socialdistance of 8, however, on the user's home page, friends at a socialdistance of 2 or less are only displayed. As another example, the socialmap may include the 100 closest friends, however, on the user's homepage, only the top 10 friends (i.e. 10 users with the smallest socialdistance) are displayed.

In one embodiment of the present invention, one option allows the buyerto request viewing classified advertisements, step 360. In suchembodiments, any number of filters, described below may be entered bythe buyer. In other embodiments, classified advertisements may beautomatically requested for the buyer on their home page.

In one embodiment of the present invention, in response to the request,a restricted number of classified listings are retrieved from the wholeclassified list, step 370. In one embodiment, only the classifiedlistings of users within the buyer's the social map are retrieved frommemory. In another embodiment, classified listings of users less than athreshold social distance (e.g. 6) from the buyer are retrieved frommemory. In yet another embodiment, classified listings of apredetermined number of closest users may be retrieved. In still otherembodiments, classified listings may be based upon affinity group socialdistance.

In other embodiments, the restricted number of classified listings mayexclude classified listings of users in the buyer's social map, andinclude classified listing of users outside the buyer's social map.Further, the classified listings of users within a determined socialdistance (e.g. 2) are excluded and classified listings of users greaterthan a determined social distance (e.g. 2) away are included. In yetanother embodiment, classified listings of a predetermined number ofclosest users (e.g. 500) are excluded, and classified listings of usersgreater than the predetermined number (e.g. 500) of closest users arespecifically included. Such embodiments are believed useful if the userwants to draw from “outside the box,” for privacy concerns, or the like.

In various embodiments, additional filtering criteria may furthernarrow-down classified listings presented to the user, step 380. Forexample, other types of limitations may be used to filter-out classifiedlistings, for example, geographic area of the poster, age of the poster,other demographics of the poster, family status of the poster, whetherthe poster is an individual or a group (e.g. company), and the like. Inlight of the present patent disclosure, it is believed that one ofordinary skill in the art would recognize that many different marketingcriteria may be used as filters in embodiments of the present invention.These filters may be pre-specified by users in some embodiments, or inother embodiments, default values for filters may be provided, which theuser can override, or the like. In other embodiments, the user may beprompted for a selection of one or more selections in the classifiedlisting hierarchy as a filter. For example, the user may navigate to“Help Wanted” listing sections, “Rentals” listing sections, “SportsEquipment” listing sections, and the like.

In other embodiments of the present invention, users may also search forclassified listings based upon specified affinity groups. As an example,the user may specify searching for classified listings only within aparticular affinity group, for example searching for “cards” for sale ina “performance magic” affinity group, but not searching in a “Yu-Gi-Oh”affinity group. In some cases, the affinity groups may be groups theuser is a member of, however, in other cases, the user need not be amember of the affinity groups to view classified listings. In someembodiments, affinity groups may be organized in a hierarchy,accordingly, the social distance may be generated that specifies how farapart two affinity groups are. For example, a top-level affinity groupmay be “performance magic” and two lower-level affinity groups may be“coin magic,” and “card magic.” Similar to the above, the user mayspecify that she can see classified listings of affinity groups that areless than a particular affinity number away from a given affinity group.

In response to the specified filters, the restricted classified listingsare filtered, resulting in customized classified listings being outputto the user, step 390. As a result, classified listings that arerelevant to the user (via filters) and from “trust-worthy” sources (e.g.users with low social distance from the user) are provided. Further,classified listings from less known sources (e.g. users with highersocial distance from the user) are not provided at the same time, invarious embodiments.

In another embodiment, classified listings are automatically prioritizedand placed into a series of directories by the system. In thisembodiment, each directory may be associated with one or more socialdistance from the user. For example, one directory includes classifiedlistings on closer friends (social distance=1-2); one directory includesclassified listings of intermediate friends (e.g. friends of closerfriends, social distance=2-4); and the like. In such embodiments, auser/buyer can easily select the classified listing directory she ismost comfortable with to view. For example, classified listings fromcloser friends may automatically be provided to the buyer. Additionally,if the user wants to go beyond this group, the user may select one ormore directories that store classified listings for intermediatefriends, or further, step 400. In response, classified listings of suchusers are then provided, step 410.

In other embodiments, classified listings are automatically placed intoanother series of directories by the system based upon affinity groupmembership. Accordingly, a user/buyer can select directories of affinitygroups the user is a member of, or an affinity group the user is notmember of, but may be relevant to what is being sought by the user. Invarious embodiments, affinity groups may have a hierarchal organization,accordingly, particular affinity groups may be more closely related toeach other than two randomly selected affinity groups. In such cases,the affinity groups that are more closely related may be higher-up inthe classified listing directory hierarchy presented to the user.

In various embodiments of the present invention, fees could be chargedfor access to certain classified listings. For example, certain affinitygroups may charge users to view classified listings, archived listings,or the like. As an example, an affinity group may be similar to a“buying club” and have fees for members to join or to view particularlistings. In another example, the affinity group may be a company, andsubscription fees are required for listings of latest product versionsand download links, and the like. In such cases, such listings may beplaced in a folder that is indicated as a “premium” service, or the liketo the user. Fees may also be required for automatic classified listingmonitoring for particular goods, services, jobs, auctions, or the like.

The inventors of the present invention, believe this combination ofclassified listings in combination with social network filteringenhances the parties to trust each other for the transaction becausethey are friends of friends, and not total strangers. Accordingly, alarger number of communications between the parties are expected to takeplace and a larger number of completed transactions are expected usingembodiments of the present invention. Based upon current test data,these expectations have proven true—the effectiveness of classifiedlistings for connecting two parties has dramatically increased.

FIGS. 4A-B illustrate a flow chart according to an embodiment of thepresent invention. More specifically, FIGS. 4A-B illustrate a process ofa poster restricting display of postings using trust-based metrics.

In embodiments of the present invention, different ways to restrict theposting of classified listings are disclosed. For example, as will bedescribed below, users who post classified listings may also leveragethe relationships of the social network to target users based uponsocial distance.

Initially, a users logs into the social-network server 200, step 500.Such operations may be done with conventional user name/passwordcombination, or any other level of security. As an option to the users,the users submit hierarchal posts, step 510. In various embodiments, aserver, separate from server 200 may be used to receive the hierarchalposts. In various embodiments, hierarchal posts are again classifiedlistings, as discussed above, offering goods or services, listing jobopenings, listing auction entries, and the like.

In embodiments of the present invention, users who post classifiedlistings may also specify posting criteria for the listing based uponrelationships defined in the social network, step 520. In oneembodiment, the user/poster specifies a maximum social distance away(from the user) where the classified listing can be displayed.Accordingly, users who are within the maximum social distance areallowed to view a user's classified listing, whereas users who areoutside the maximum social distance are not allowed to view the user'sclassified listing. For example, a user may specify that an automobilefor sale will be available only to users that have a social distance ofthree or less. Such embodiments are believed beneficial to the poster,because users within the specified social distance are typicallyconsidered more trustworthy than other users. That is, potential buyerswith a small social distance are normally less likely to defraud theposter, in part due to the potential buyer's reputation in the socialnetwork.

In other embodiments of the present invention, users who post classifiedlistings may specify only posting to users within a specified tribe oraffinity group or closely related one. Accordingly, users who aremembers of the tribe are allowed to view a user's classified listing,whereas users outside the tribe are not allowed to view the user'sclassified listing. For example, a user may specify that the classifiedlisting will be available to users in a “Magic Performance” tribe, orthe like. These embodiments are believed beneficial to the poster,because if the listing is relevant to the tribe, it is more likely thatusers of that tribe will respond. Additionally, by limiting the reach ofthe classified listing (audience), it is less likely that the posterwill be accused of “spamming” others in the social network.

In other embodiments of the present invention, the poster may specifyother types of limitations may be also used to limit or target aclassified listing, for example, geographic area (e.g. San Francisco BayArea, Boston Area, 50 miles from Chicago), age, demographic (e.g. male,female, income, home owner), family status (e.g. married, divorced,married with children), and the like, step 530. In light of the presentpatent disclosure, it is believed that one of ordinary skill in the artwould recognize that many different marketing criteria may be applied toembodiments of the present invention.

In other embodiments, the viewer may, in addition, or alternatively toabove, specify that classified listings closer than a minimum socialdistance away are not potentially viewable. For example, a corporateuser may want to get “fresh blood” into the organization, and thus posta help wanted advertisement to users greater than a social distance of 2away; and at the same time, a user/job seeker may seek jobs outsidetheir industry, thus only desire to view classified listings greaterthan a social distance of 3 away. Other similar situations areimaginable with respect to other types of limitations, such asgeography, affinity group, and the like.

In various embodiments, fees may be charged to the posting user basedupon social distance, affinity group, or the like. For example, forfree, the user may make a classified listing be available to users aspecified social distance of one away (i.e. immediate friends), membersof the same affinity group as the user, users within a particulargeographic area, and the like. If the user is willing to pay a fee, theuser may make a classified listing be available to users outside the“free” posting area. For example, the classified listing may be postedfor free to users within a social distance of three, but the classifiedlisting may be posted to users within a social distance of up to six fora fee. In another example, for a fee, the classified listing may bepresented to users, in a wider geographic area, to a larger number ofrelated-affinity groups, and the like.

In additional embodiments, it is contemplated that viewers of classifiedlistings may themselves may recommend or forward classified listings toother users. For example, a first user may view a classified listing fora job and forward the listing to a second user who may be looking for ajob. The second user may also forward the classified listing to anotheruser, and so on. In embodiments of the present invention, limits may beapplied to whom a user may forward classified listings to, to avoid“spam” problems with mass forwarding of classified listings. As anexample, viewers of classified advertisements may be limited toforwarding classified listings to users of a social distance of one, twoor the like away.

In addition, in some embodiments, classified listing users may limit theforwarding of their classified listings to other users. For example, aposter may specify that the classified listing is available to userscloser than a social distance of 2.5, and that the classified listingcan be forwarded only to users closer than a social distance of 4, orthe like. Additionally, from a receiving end, the users who received theforwarded classified listing may decide to filter-out the forwarded orrecommended classified listings from users greater than a specifiedsocial distance away (e.g. three or greater.)

In other embodiments, a poster may compensate or pay fees for viewers toforward classified advertisements to other users. For example, a postermay post a job listing, and a first viewer may view the job listing andforward it to a second viewer. If the second user is fit for the job andhired, the poster may pay a referral fee to B. This process may betermed “Pay It Forward” enables bounties to be paid to participants inthe communication chain leading to fulfillment of the classifiedadvertisement. Embodiments may be paid for a product being sold, aperson being hired, an apartment being rented, or the like. In otherembodiments, simply forwarding the advertisement to another user itselfmay trigger some sort of compensation. Types of compensation can includemonetary payment, user access to protected content (e.g. articles,music, film clips), coupons, membership, or the like.

In various embodiments of the present invention, the classifiedadvertisement along with the desired social network filtering criteria,as well as additional filtering criteria are stored and associated withthe poster, step 540.

In various embodiments, when a subsequent user requests classifiedlistings, step 550, the system determines when the social networkcriteria, the filtering criteria, and/or the forwarding limitations ofthe poster are satisfied, step 560. If not, the listing is not providedto the subsequent user, step 590.

In various embodiments, the system then determines whether theclassified listing meets the subsequent viewer's social networkcriteria, filtering criteria, as was described above, step 570. If so,the classified listing may be provided to the viewer, step 580. As canbe seen, criteria of the poster and criteria of the viewer should besatisfied before the viewer can see the classified listing. As examples,a poster may post a job listing for a programmer to users within asocial distance of three, with a forwarding maximum social distance offive. Further, a job hunter may look for programming jobs from posters amaximum social distance of two away. If a social distance from theposter to the viewer is four, the viewer may not see the job listingunless it is forwarded to her; if the social distance from the viewer tothe poster is three, the viewer may not see the job listing; if thesocial distance from the poster to the viewer is three, and the socialdistance from the viewer to the poster is two, the viewer may see thejob listing; and the like.

In the illustrated example, if the viewer's criteria are not met, theclassified listing is not initially provided to the viewer, step 600,but is placed in a lower priority folder. The viewer may request to viewthe listing at a later time.

In additional embodiments, advertisements or classified listings can bespecifically targeted by posters to viewers or affinity groups basedupon demographic criteria, affinity data, and the like. Similarly,viewers can explicitly state the types of specific advertisements theyare receptive to receiving, by specifying an interest, joining a groupor affinity group relevant to the specific advertisements. Thecombination of these features allows advertisers to target highlyrelevant classified listings to receptive viewers.

In embodiments of the present invention, combining advertisementtargeting with “Tribe Mapping,” discussed above, it is believed thatposters can more easily determine potentially interested viewers. Forexample, a poster is trying to present advertisements to 10,000 wineenthusiasts, however the Wine Tribe includes only 1,000 users. In thiscase, by finding closely related tribes to the Wine Tribe, based uponuser membership, the remaining 9,000 users may be identified. Forexample, closely related tribes could include a “Gourmet Food Tribe,”“Resort Living Tribe,” and the like. Although not all members of therelated tribes may be interested in wine, by providing suchadvertisements to related tribe members is believed to yield betterresults than random advertisement placement.

In additional embodiments of the present invention, additional filteringfactors may be used, in step 380 and 530, above. In various embodiments,“reliability,” “feedback,” “reputation,” “star rating” factors, or thelike may be specified. These reliability factors may be based on anynumber of criteria, such as reliability in responding to questions, indelivery of goods or services, in quality of services, in timeliness ofresponse, in satisfaction, in length of membership, amount of time inbusiness, forum participation and behavior, and the like. Thesereliability factors, alone, are often not trusted by viewers. Theinventors believe this is because viewers do not know whether theopinions are trustworthy or not (i.e. ratings by shills). Accordingly,the addition of social network criteria help provide the viewer with atrust-metric to enable them to make more informed decisions. Becauseeach buyer has their own unique social map, the social distances of theraters of a merchant or seller, tend to be unique.

In various embodiments, the trust-metric (e.g. social distance) may be avalue that is independently presented to the viewer, along with therating value. In other embodiments, the trust-metric value and therating value may be combined in any number of ways to provide a singlevalue. For example, the single value may be a simple average of therating and trust-metric value, a weighted combination, a non-linearcombination, or the like.

As examples of embodiments of the present invention, an implementationof the above social networking overlay could be implemented inconjunction with e-commerce sites, such as an auction site such asebay.com, amazon.com, or the like. In such embodiments, reliability ofthe buyers and sellers can be adjudged based upon feedback from priorsellers and buyers, respectively, and now also based upon 1) socialdistance of the raters and/or 2) social distance of the buyer or sellerin question. As examples of the first case, a buyer may be inclined tobuy from a small, high-rated seller with raters at a social distance of2.1 away rather than a higher-rated seller with raters at a socialdistance of 6.4 away; a buyer may be inclined to buy from a highly-ratedseller with raters at a social distance of 3.2 away at a higher pricethan a higher-rated seller with raters at a social distance of 4.5 away;or the like. As examples of the second case, a first seller is at asocial distance of 2 from a potential buyer, and a second seller is at asocial distance of 3 from a potential buyer. If the first seller has a 4star rating, and the second seller has a 3 star rating, the first sellerwill be ranked ahead of the second seller; if the first seller has a 2star rating, and the seller has a 4 star rating, the second seller maybe ranked ahead of the first seller; and if the first seller has a 3star rating, and the seller has a 3 star rating, the first seller may beranked ahead of the second seller; or the like.

An another example, trust-metric data could be used in conjunction withrecommendation sites, such as epinions.com, zagat.com, aaa.com, or thelike. In some embodiments, the trust-metrics may be the social distanceof users who rate product quality, restaurants, hotels, airlines, andthe like. As examples, a user may prefer to buy a product with a threestar rating rated by others at a social distance of 2.1 rather than aproduct with a three and a half star rating rated by others at a socialdistance of 3.5; a user may prefer to see a movie with four “thumbs-up”rating by others at a social distance of 4.2 rather than a movie withthree “thumbs-up” rating by others at a social distance of 1.5; and thelike. In various embodiments, one way to present such results is bystating users within a first social distance (e.g. 1-2) rate thisproduct with X stars (e.g. 4 stars); users within a second socialdistance (e.g. 2-3) rate this product with Y stars (e.g. 3.5 stars);users within a third social distance (e.g. 3-6) rate this product with Zstars (e.g. 3.3 stars).

In various embodiments of the present invention, a user's profile can beaugmented by data that is available on other social networks andportals. Reliability or trust of the user can thus be obtained from anumber of domains. For example, a user may have an excellent forumrating because of the user's timeliness and usefulness of postings. Thisinformation can be used in the context of classified listings. Forexample, a potential buyer may base their buying decision on the user'sforum reputation, as a proxy for the classified listing reputation. Theinventors believe this solution solves a problem with seller ratings onsites such as e-Bay, because sellers with little transaction history areat a disadvantage compared to e-Bay volume sellers (e.g. businesses.)Accordingly, using a proxy for trustworthiness provides a levelplaying-field for individuals to penetrate such “power law” reputationnetworks (where power becomes more concentrated in the first movers).

In various embodiments, data from other domains may be imported orlinked to the user's profile. As an example, a user's e-Bay sellerrating may be made available on her profile by either importing thatvalue, or by an external link to such content. This aggregation ofsocial information from a collection of separate locations can giveothers a better idea of the user's social standing. For example, thedata may include tribe membership, interests, blog posts, forum ratings,seller ratings, buyer ratings, philanthropic donations, memberships inexternal organizations (e.g. WWF, IEEE, Mensa), and other externalcontent (e.g. Amazon Wishlist). In various embodiments, a reliabilityrating of a buyer or seller in a classified listing context may thus bedetermined upon the user's, e-bay seller rating, Amazon seller rating,e-pinions forum reputation, and the like.

In embodiments of the present invention, another novel concept is thatthe relationship data of users stored in the social network may beexported to many different applications, such as genealogy, organizationhistory, leadership charts, or the like. Further, the user relationshipdata may also be exported to different social networks, or the like. Inother embodiments of the present invention, the user relational data maybe imported into social networks, such as customer lists, or otherapplication or service that stores identity information. In general, theuser's profile and social relationships can be distilled into a flatfile outside of the social network, portal, or the like, that can be“carried around” by the user and can be controlled by the user.Additionally, embodiments allow the user to unify aspects of the user'sidentity in one or more files in a single location, whereas previously,the user's identity was distributed in multiple locations, such asyahoo!, eBay, or the like. In one embodiment, the user's profile isdescribed in a format termed FOAF (Friend of a Friend), a flat XMLdocument, including RDF descriptions of ontologies.

In other embodiments of the present invention, other types of data otherthan classified listings or posts may be restricted or prioritized basedupon trust-metric criteria. In one example, the social networkingfactors could be implemented in conjunction with search engines such asYahoo, Google, MSN search, and the like. In some embodiments, clicks onlinks by previous users may be combined with the trust-metric values todetermine a priority for search results. For example, a first user is amember of an affinity group such as an “toy airplane affinity group,”and a second user is a member of a “fashion affinity group.” If thefirst user searches for the terms “model” and “photography,” the searchengine may initially identify a number of search result links.Subsequently, based upon selected search result links of other membersin the same “toy airplane affinity group,” the search engine willpromote links about “hobby supplies,” “macro photography,” “aviation”and the like, for the first user. In contrast, if the second usersearches for the same terms “model” and “photography,” the search enginemay again identify the same number of search result links. However,based upon selected search result links of other members in the “fashionaffinity group,” the search engine may promote links about “photographicsupplies,” “fashion models,” “weight loss supplements” and the like, forthe second user.

As another example, a search engine may prioritize results based uponprior searches performed by users closer than a determined distance awayfrom the user. For example, a college student may search for “airlines”and “hotels.” In such embodiments, the search engine may identifypotential links to return to the student, then, based upon searchesperformed by users less than a social distance of two away, for example,the college student's results may be prioritized. If many of thestudent's friends are planning trips to Ft. Lauderdale, the searchresults may prioritize links describing “Spring Break packages toFlorida,” “Miami nightlife guides” “tanning salons” and the like.

In light of the present disclosure, one of ordinary skill in the artwill recognize that many other types of collaborative filteringtechniques may be advantageously adapted with the trust-metric factorsdescribed above.

In other embodiments of the present invention, users need not log intothe social network, but instead may receive classified listings throughsubscriptions to listing feeds via RSS, or the like. Other methods forsyndication of listings to other networks and providers arecontemplated, for example cell phone networks, PDA and/or pagernetworks, and the like. As other examples, embodiments may be applied topeer to peer classified listings where feeds, subscriptions, and queriesflow through a chat or P2P clients without a portal in the middle. Insuch embodiments, users may specify one or more subscriptions thatinclude a persistent search via RSS, subscriptions that monitor one ormore channels for any data, or the like. In response, when the one ormore feeds include data satisfying the search, or when data is posted onthe channel, the respective data is provided to the user. For example, auser may specify a search such as, “apartments in Mountain View” whichsearches a real-estate feed, or may specify monitoring a channel titled“Mountain View apartments.”

Generally, embodiments allow for portal-less communication and commercetransactions from device to device, or peer to peer, without having tovisit an intervening portal. In such embodiments, users may postclassified listings to the “network of listening devices” and users mayview classified listings with a “listening device” both without centralportal (e.g. Craigslist.org, ebay.com).

In various embodiments of the present invention, any combination of theabove techniques is contemplated. Further, in embodiments, the resultsdisplayed to the user may be non-prioritized, or may be prioritizedbased upon the filtering criteria. For example, classified listings maysimultaneously be presented to a user/viewer via folders or via positionin a hierarchy listing based upon social distance, based upon affinity,reliability, and the like. In various embodiments, when a socialnetworking filter is applied to user recommendations (for example, userswho are rating a service provider, such as a plumber), recommendationsfrom a user's social network can be highlighted to the user. Forexample, if several friends have recommended the same plumber, thatplumber may appear as a “recommendation from my social network” to theuser. As another example, social network metrics, such as a socialdistance, and a poster rating may be used with or without usingadditional filtering criteria, for both posters and potential buyers.Accordingly, any of the above embodiments are not exclusive.

Embodiments of the present invention may be applied to any number ofhierarchal posting/classified listing embodiments. For example,embodiments may be used in conjunction with any on-line shopping searchsystem such as froogle.com, mysimon.com, or the like. In addition,embodiments may be used in conjunction with on-line shopping ratingsystem such as epinions.com, bizrate.com, or the like. Embodiments mayalso be based upon brick-and-mortar shopping systems, such as registryservices provided by stores, and the like. The above embodiments mayalso be applied to on-line merchants such as amazon.com, bn.com,overstock.com and the like. Additionally, as discussed above,embodiments may be applied to auction sites such as ebay.com, and thelike. Accordingly, the concepts disclosed above are extremely valuablein a variety of applications, such as interactive “yellow pages” anddirectories of products and services (e.g. Thomas Register,Martindale-Hubbell), and the like.

In the embodiments disclosed above, and in the claims below, referenceis made as to the trust relationships between two users, however, itshould be understood that the trust relationships can span more than twousers. For example, in value chains including multiple users, such as aseller, a value added reseller, and a buyer, the trust relationships ofeach party is important. This is even more significant for more complexvalue chains with multiple participants.

Further embodiments can be envisioned to one of ordinary skill in theart after reading this disclosure. In other embodiments, combinations orsub-combinations of the above disclosed invention can be advantageouslymade. The specification, accordingly, is to be regarded in anillustrative rather than a restrictive sense. It will, however, beevident that various modifications and changes may be made thereuntowithout departing from the broader spirit and scope of the invention asset forth in the claims.

1. A method to be executed by a computer system operating in a networkenvironment in which Internet Protocol (IP) packets are exchanged,comprises: receiving a hierarchal post from a first user; receiving afiltering criteria associated with the hierarchal post from the firstuser; determining a first plurality of social network relationshipfactors for the first user with respect to a first plurality of users,wherein a first profile is provided for the first user and includes afirst social distance between the first user and a second user, andwherein the first social distance is reduced between the first andsecond users as a result of a weighting factor that is determined by afrequency of communications between the first and second users, aresponsiveness by the first user in answering communications from thesecond user, and by a manual adjustment made directly to the weightingfactor by the first user; determining a second plurality of users inresponse to the first plurality of social network relationship factors,from the first plurality of users who fulfill the filtering criteria,wherein a third plurality of users from the first plurality of users donot fulfill the filtering criteria; making the hierarchal post availableto users from the second plurality of users but not the third pluralityof users; and providing the hierarchal post to the second user from thesecond plurality of users, wherein each of the posts are identified ashaving been submitted by an individual user, and wherein the hierarchalpost is selected from a group consisting of classified listings, joblistings, auction listings, listings of goods, listings of services, andlistings of real estate.
 2. The method of claim 1 wherein the first usercomprises an entity selected from the group consisting of: anindividual, a company, a partnership, a business, a group ofindividuals.
 3. The method of claim 1 further comprising: determining apre-determined filtering criteria; receiving a request from the firstuser to modify the pre-determined filtering criteria; and determining asecond filtering criteria in response to the pre-determined filteringcriteria and in response to the request.
 4. The method of claim 3wherein a fourth plurality of users from the first plurality of usersfulfill the pre-determined filtering criteria; and wherein a number ofusers in the second plurality of users is greater than a number of usersin the fourth plurality of users.
 5. The method of claim 1 wherein thefirst plurality of social network relationship factors comprise socialdistance values; and wherein the filtering criteria comprises a socialdistance value selected from a group consisting of a maximum socialdistance value, a minimum social distance value.
 6. The method of claim1 further comprising determining the first plurality of users from afourth plurality of users who are within a set of social distance awayfrom the first user.
 7. A computer system comprises: a memory configuredto store relationships between a first plurality of users; and aprocessor coupled to the memory wherein the processor is configured toreceive a first classified advertisement listing from a first user,wherein the processor is configured to determine social distances fromthe first user to the first plurality of users, wherein the processor isconfigured to determine a social network criteria in response to inputfrom the first user, the social network criteria dependent on the socialdistances from the first user to the first plurality of users, wherein afirst profile is provided for the first user and includes a first socialdistance between the first user and a second user, and wherein the firstsocial distance is reduced between the first and second users as aresult of a weighting factor that is determined by a frequency ofcommunications between the first and second users, a responsiveness bythe first user in answering communications from the second user, and bya manual adjustment made directly to the weighting factor by the firstuser, wherein the processor is configured to determine a secondplurality of users in response to the social distances, from the firstplurality of users who fulfill the social network criteria, wherein theprocessor is configured to provide the first classified advertisementlisting to users from the second plurality of users, wherein theprocessor is configured to suppress the first classified advertisementlisting from users from a third plurality of users from the firstplurality of users who do not fulfill the social network criteria,wherein each of the listings are identified as having been submitted byan individual user, and wherein the first classified advertisementlisting from the first user is selected from a group of listingsconsisting of job listings, auction listings, listings of goods,listings of services, and listings of real estate.
 8. The computersystem of claim 7 wherein the first user comprises an entity selectedfrom the group consisting of: an individual, a company, a partnership, abusiness, a group of individuals, an affinity group, a tribe.
 9. Thecomputer system of claim 8 wherein the social network criteriacomprises: a social distance in relationship to a modified socialdistance; wherein the processor is also configured to determine apre-determined social distance; wherein the processor is also configuredto receive a request from the first user to modify the pre-determinedsocial distance; and wherein the processor is configured to determinethe modified social distance in response to the pre-determined socialdistance and in response to the request.
 10. The computer system ofclaim 6 wherein the relationship is selected from a group ofrelationships consisting of: less than, greater than, equal to.
 11. Thecomputer system of claim 10 wherein the processor is configured todetermine social distances from the first user to the first plurality ofusers in response to the relationships between the first plurality ofusers.
 12. The computer system of claim 7 wherein the processor is alsoconfigured to receive a request from the second user from the thirdplurality of users; and wherein the processor is configured to providethe first classified advertisement listing to second user from the thirdplurality of users in response to the request.
 13. A computer programproduct comprising a tangible media comprising executable code for acomputer system including a processor includes: code that directs theprocessor to determine an advertisement listing from a first user; codethat directs the processor to determine a first plurality of socialnetwork relationship factors for the first user with respect to a firstplurality of users; code that directs the processor to determine afiltering criteria in response to input from the first user, thefiltering criteria dependent on the first plurality of social networkrelationship factors; code that directs the processor to determine asecond plurality of users in response to the first plurality of socialnetwork relationship factors, from the first plurality of users whofulfill the filtering criteria, wherein a third plurality of users fromthe first plurality of users do not fulfill the filtering criteria,wherein a first profile is provided for the first user and includes afirst social distance between the first user and a second user, andwherein the first social distance is reduced between the first andsecond users as a result of a weighting factor that is determined by afrequency of communications between the first and second users, aresponsiveness by the first user in answering communications from thesecond user, and by a manual adjustment made directly to the weightingfactor by the first user; code that directs the processor to determinerequests for advertisement listings from users from the first pluralityof users; and code that directs the processor to provide theadvertisement listing to users from the second plurality of users inresponse to the requests, but not to users from the third plurality ofusers in response to the requests, wherein each of the listings areidentified as having been submitted by an individual user, and whereinthe advertisement listing is selected from a group of listingsconsisting of: classified listings, job listings, goods listings,services listings, and auction listings; wherein the codes reside on atangible media.
 14. The computer program product of claim 13 wherein thefirst plurality of social network relationship factors includes aplurality of social distances from the first user with respect to usersfrom the first plurality of users; wherein the filtering criteriaincludes a set social distance; wherein the code that directs theprocessor to determine a second plurality of users from the firstplurality comprises code that directs the processor to determine usersfrom the first plurality of users that have a social distance in arelationship to the set social distance; and wherein the relationship isselected from a group of relationships consisting of: greater than, lessthan, equal to.
 15. The computer program product of claim 14 furthercomprising: code that directs the processor to determine the set socialdistance in response to input from the first user.
 16. The computerprogram product of claim 14 wherein the first user comprises a group ofusers; and wherein the plurality of social distances from the first userwith respect to users from the first plurality of users comprises asmallest social distance between users from the group of users to usersfrom the first plurality of users.
 17. The computer program product ofclaim 13 further comprising: code that directs the processor todetermine an advertisement listing from the second user; code thatdirects the processor to determine a second plurality of social networkrelationship factors for the second user with respect to the firstplurality of users; code that directs the processor to determine a thirdplurality of users from the first plurality of users who fulfill anotherfiltering criteria, wherein a fourth plurality of users from the firstplurality of users do not fulfill the other filtering criteria; codethat directs the processor to determine requests for advertisementlistings from users from the third plurality of users; and code thatdirects the processor to provide the advertisement listing to the usersfrom the third plurality of users in response to the requests, but notto users from the fourth plurality of users in response to the requests;wherein the second plurality of users and the third plurality of usersare not identical.